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Ioannis Patras

Researcher at Queen Mary University of London

Publications -  233
Citations -  9547

Ioannis Patras is an academic researcher from Queen Mary University of London. The author has contributed to research in topics: Computer science & Feature extraction. The author has an hindex of 36, co-authored 210 publications receiving 7486 citations. Previous affiliations of Ioannis Patras include University of Hong Kong & University of Crete.

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DEAP: A Database for Emotion Analysis ;Using Physiological Signals

TL;DR: A multimodal data set for the analysis of human affective states was presented and a novel method for stimuli selection is proposed using retrieval by affective tags from the last.fm website, video highlight detection, and an online assessment tool.
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Dynamics of facial expression: recognition of facial actions and their temporal segments from face profile image sequences

TL;DR: This paper presents a system for automatic recognition of facial action units (AUs) and their temporal models from long, profile-view face image sequences and introduces facial-action-dynamics recognition from continuous video input using temporal rules.
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AMIGOS: A Dataset for Affect, Personality and Mood Research on Individuals and Groups

TL;DR: The database allows the multimodal study of the affective responses of individuals in relation to their personality and mood, and with respect to the social context and videos’ duration, and presents a detailed correlation analysis of the different dimensions.
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Spatiotemporal salient points for visual recognition of human actions

TL;DR: This paper addresses the problem of human-action recognition by introducing a sparse representation of image sequences as a collection of spatiotemporal events that are localized at points that are salient both in space and time.
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DECAF: MEG-Based Multimodal Database for Decoding Affective Physiological Responses

TL;DR: DECAF is presented, a detailed analysis of the correlations between participants' self-assessments and their physiological responses and single-trial classification results for valence, arousal and dominance are presented, with performance evaluation against existing data sets.